It is our contention that comparisons of locations for non-identical population is a common problem in medical and biological research. When this can occur, the statistical procedures must account for, and adjust the analysis appropriately. We propose a solution to the two-sample location problem, where the parent populations are continuous and symmetric but not necessarily identical. The statistic to be used is a modification of the Mann-Whitney-Wilcoxon Statistic. We use a non-linear rank statistic, which is a consistent estimator of variance of the Mann-Whitney-Wilcoxon, to standardize the classical statistic. This new statistic is distribution-free if the population are identical and asymptotically distribution-free if they have the same location but are not identical. We conjecture that the Bahadur efficiency of the modification relative to the usual test is greater than one for a large class of distributions. We propose a simulation study to discover the small sample properties of this modification and to compare it to a number of the classical procedures. Subsequent work will extend this procedure to the k-sample location problem and other experimental designs.